Powertrain control system

Abstract

Systems and methods are described for powertrain controls optimization. One method comprises adaptively learning engine settings for a sparse sample of a speed-load map, which includes engine operation at boundary conditions of a speed-load map, and generating a dynamic node look-up table based on the learned engine settings for the sparse sample. The dynamic node look-up table may provide engine settings for engine operation at speed-load points not explicitly learned during the adaptive learning.

The invention claimed is: 
     
       1. A method for an engine, comprising:
 during operation of the engine:
 learning a first set of engine actuator settings, including current positions or timings of engine actuators, while operating at boundary conditions of a speed-load map and adaptively adjusting the learned first set of engine actuator settings to provide a desired engine output; 
 generating a dynamic node look-up table (DLUT) based on the adaptively adjusted first set of engine actuator settings; 
 determining a second set of engine actuator settings for operation at non-boundary conditions of the speed-load map from the DLUT and not learning and adaptively adjusting the second set of engine actuator settings; and 
 controlling engine actuators to the second set of engine actuator settings during operation of the engine at the non-boundary conditions. 
 
 
     
     
       2. The method of  claim 1 , wherein the boundary conditions of the speed-load map include one of minimum speed at any engine load, maximum speed at any engine load, minimum load at any engine speed, and maximum load at any engine speed and wherein the learning the first set of engine actuator settings is responsive to operating the engine at an engine speed and engine load that is at one of the boundary conditions of the speed-load map. 
     
     
       3. The method of  claim 1 , wherein the second set of engine actuator settings includes one or more of throttle position, spark timing, intake cam timing, and exhaust cam timing. 
     
     
       4. The method of  claim 1 , wherein the second set of engine actuator settings produces the desired engine output, the desired engine output including one or more of engine load, brake specific fuel consumption, and crank angle for 50% burn and wherein adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes adjusting one or more of the engine actuators to adjust one or more engine actuator settings to achieve the desired engine output. 
     
     
       5. The method of  claim 4 , wherein the second set of engine actuator settings reduces the brake specific fuel consumption. 
     
     
       6. The method of  claim 1 , wherein the DLUT is generated by a collection of linear models, wherein generating the DLUT includes using the collection of linear models to interpolate from the learned and adaptively adjusted first set of engine actuator settings to determine the second set of engine actuator settings and storing the determined second set of engine actuator settings in the DLUT, and wherein the first set of engine actuator settings are learned from preprogrammed or previously learned engine actuator settings. 
     
     
       7. The method of  claim 1 , wherein the engine is a naturally aspirated engine and wherein determining the second set of engine actuator settings from the DLUT includes, in response to operating the engine at the non-boundary conditions of the speed-load map, interpolating between the adaptively adjusted first set of engine actuator settings at the boundary conditions to generate the second set of engine actuator settings at the non-boundary conditions. 
     
     
       8. The method of  claim 1 , where the generated DLUT includes adaptively learned engine actuator settings for engine speed and engine load values that are at the boundary conditions of the speed-load map and engine actuator settings that are not adaptively learned at the non-boundary conditions of the speed-load map, where the engine actuator settings that are not adaptively learned are determined and stored within the DLUT according to one or more engine models that use the adaptively learned engine actuator settings as inputs. 
     
     
       9. The method of  claim 1 , wherein adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes adjusting two or more of the engine actuators to adjust two or more engine actuator settings to achieve the desired engine output, where adjusting the two or more engine actuators includes adjusting two or more of a throttle position of a throttle, spark timing of a spark plug, intake cam timing of an intake valve, exhaust cam timing of an exhaust valve, a position of an exhaust gas recirculation valve, and a position of a wastegate. 
     
     
       10. The method of  claim 1 , wherein learning the first set of engine actuator settings and adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes commanding the engine to operate at engine speeds and engine loads that are at different boundary conditions of the speed-load map while varying the engine actuators to achieve a desired mean brake torque and reduced brake specific fuel consumption. 
     
     
       11. The method of  claim 1 , further comprising adaptively adjusting the learned first set of engine actuator settings in parallel with generating the DLUT based on the adaptively adjusted first set of engine actuator settings, as the engine operates at different boundary conditions of the speed-load map. 
     
     
       12. The method of  claim 1 , wherein adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes simultaneously adjusting two or more engine actuators to achieve a desired engine load while simultaneously minimizing brake specific fuel consumption. 
     
     
       13. The method of  claim 1 , wherein adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes simultaneously adjusting two or more engine actuators to simultaneously achieve each of a desired engine load, brake specific fuel consumption, and burn ratio. 
     
     
       14. A method for an engine, comprising:
 during operation of the engine:
 learning a first set of engine actuator settings, which include current positions or timings of engine actuators, while operating at an engine speed and engine load that are at boundary conditions of a speed-load map and adaptively adjusting the learned first set of engine actuator settings, via adjusting the positions or timings of the engine actuators, based on a desired engine output, the desired engine output including one or more of a desired burn ratio, brake specific fuel consumption, and mean brake torque; 
 generating a dynamic node look-up table (DLUT) based on the adapted settings, the DLUT including adaptively learned engine actuator settings for engine speed and engine load values that are at the boundary conditions of the speed-load map and engine actuator settings that are not adaptively learned at non-boundary conditions of the speed-load map; 
 determining a second set of engine actuator settings for operation at the non-boundary conditions of the speed-load map from the DLUT for which no learning and adaptive adjusting is conducted; and 
 controlling engine actuators to the second set of engine actuator settings during operation of the engine at the non-boundary conditions. 
 
 
     
     
       15. The method of  claim 14 , wherein adaptively adjusting the learned first set of engine actuator settings to provide the desired engine output includes simultaneously adjusting two or more engine actuators to achieve a desired engine load while simultaneously minimizing brake specific fuel consumption.